The Role of Bias in Machine Learning Predictions

One of the key issues in using machine learning models to predict the success of women-led startups is the potential for built-in biases within the training data. If the historical data reflects a bias against women entrepreneurs—such as lower funding levels or fewer success stories—models may inadvertently perpetuate these patterns. Addressing these biases through careful data selection and model monitoring is essential for fair and accurate predictions.